CN108881825A - Rice weed monitoring unmanned system and its monitoring method based on Jetson TK1 - Google Patents
Rice weed monitoring unmanned system and its monitoring method based on Jetson TK1 Download PDFInfo
- Publication number
- CN108881825A CN108881825A CN201810613214.4A CN201810613214A CN108881825A CN 108881825 A CN108881825 A CN 108881825A CN 201810613214 A CN201810613214 A CN 201810613214A CN 108881825 A CN108881825 A CN 108881825A
- Authority
- CN
- China
- Prior art keywords
- unmanned plane
- module
- transparent transmission
- control station
- wireless transparent
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/183—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a single remote source
- H04N7/185—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a single remote source from a mobile camera, e.g. for remote control
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/14—Relay systems
- H04B7/15—Active relay systems
- H04B7/185—Space-based or airborne stations; Stations for satellite systems
- H04B7/18502—Airborne stations
- H04B7/18506—Communications with or from aircraft, i.e. aeronautical mobile service
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/025—Services making use of location information using location based information parameters
Abstract
The invention discloses a kind of rice weed monitoring unmanned systems and its monitoring method based on Jetson TK1, its system includes unmanned plane and ground control station, the winged control module based on Jetson TK1 is provided on the unmanned plane, first wireless transparent transmission module and image capture module, the first wireless transparent transmission module and image capture module are electrically connected with winged control module respectively, described image acquisition module includes GOPRO camera and image pick-up card, the ground control station includes the end PC earth station and the second wireless transparent transmission module, the second wireless transparent transmission module and the end PC earth station are electrically connected, the ground control station is communicated wirelessly and is connect by the first wireless transparent transmission module and the second wireless transparent transmission module with winged control module.The present invention can analyze collected realtime graphic in real time, improve working efficiency, and the distribution situation of weeds and menace level can be shown in the offline map of ground control station, have intuitive and convenience.
Description
Technical field
The present invention relates to the technical fields of rice weed image recognition, refer in particular to a kind of rice based on Jetson TK1
Weeds monitoring unmanned system and its monitoring method.
Background technique
Rice weed brings serious harm to the growth of rice, and weeds can absorb nutrient around rice, moisture etc., and
And can the sunlight air to neighbouring rice have an impact, directly affect the growing way of rice, weeds quantity is more, and rice growing way is got over
It is weak.In order to solve the problems, such as accurate weeding by realizing the variable spray of herbicide, remote sensing images are acquired using unmanned plane, are made
Identify that weeds are always research hotspot with image recognition technology.
Due to identifying that weeds need by a large amount of mathematical computations by image processing techniques, so generally to processor
It is required that very high.Traditional solution is to obtain the remote sensing images in corresponding rice region under the operation that unmanned plane passes through user,
It is to be collected it is complete after, the remote sensing images that will acquire are taken off from the reservoir on unmanned plane, use server carry out image knowledge
Other places reason, it is efficient to be then unfavorable for user to the rice weed region marking of processing image by manual type in this way
Ground, in real time, intuitively observe weed identification result.As the technology of precision agriculture continues to develop, applied to agricultural aviation
Remote sensing images acquisition and requirement of the identification technology to real-time and convenience are higher and higher, traditional remote sensing images acquisition and identification
Technology is no longer satisfied the demand of precision agriculture, knows so seeking efficient, the general rice weed image that is based in real time of one kind
Not Jian Ce system and scheme to meet the requirement of precision agriculture be a current urgent problem.
Summary of the invention
It is an object of the invention to overcome the deficiencies in the prior art, propose it is a kind of efficiently, reliably based on Jetson
The rice weed monitoring unmanned system and its monitoring method of TK1, can monitor and identify rice weed in real time, to meet accurate agriculture
The requirement of industry.
To achieve the above object, technical solution provided by the present invention is as follows：
Rice weed monitoring unmanned system based on Jetson TK1, including unmanned plane and ground control station, the nothing
It is provided with winged control module, the first wireless transparent transmission module and image capture module based on Jetson TK1 on man-machine, described first
Wireless transparent transmission module and image capture module are electrically connected with winged control module respectively, and described image acquisition module includes that GOPRO takes the photograph
As head and image pick-up card, the ground control station includes the end PC earth station and the second wireless transparent transmission module, and described second is wireless
Transparent transmission module and the end PC earth station are electrically connected, and the ground control station and fly control module and pass through the first wireless transparent transmission module and the
Two wireless transparent transmission modules communicate wirelessly connection.
The unmanned plane is equipped with GPS.
The monitoring method of rice weed monitoring unmanned system based on Jetson TK1, includes the following steps：
Before S1, unmanned plane take off, monitoring area first delimited using the map function of the ground control station of independent development, and really
Determine flying height；
S2, ground control station automatically generate unmanned plane during flying course line and need to carry out image and adopt according to monitoring area delimited
Several destinations of collection, to guarantee that the image-capture field of GOPRO camera can cover full wafer monitoring area；
S3：Ground control station sends instruction of taking off, after unmanned plane takes off, according to airline operation pre-planned；
S4：Unmanned plane obtains the GPS position information of next destination, flight to next destination；
S5：Unmanned plane hovers after reaching predetermined destination, the paddy field region that driving image capture module acquires needs into
Row Image Acquisition, the winged control module based on Jetson TK1 are analyzed acquired image information in real time, are judged whether there is
Weed regions judge weed density grade, and the GPS position information and rating scale information are passed back if there is weed regions
Ground control station, after information is sent completely, unmanned plane then continues flight to next predetermined destination；
S6：Step S4, S5 is repeated, until unmanned plane completes all predetermined destinations；
S7：Ground control station passes through the GPS position information and density rating information for all weed regions passed back, passes through QT
With the live-action map demarcated in earth station's client that interacts of JAVASCRIPT.
Compared with prior art, the present invention having the following advantages that and beneficial effect：
1, collected realtime graphic can be analyzed in real time, improve working efficiency.
2, the distribution situation of weeds and density rating information can be shown in the offline map of ground control station, have intuitive
And convenience.
Detailed description of the invention
Fig. 1 is the structural principle block diagram of present system.
Fig. 2 is the unmanned plane simulated flight route map of present system.
Fig. 3 is the relational expression that test camera obtains rice weed region GPS coordinate on the unmanned plane provided in embodiment
Schematic diagram.
Specific embodiment
The present invention is further explained in the light of specific embodiments.
As shown in Figure 1, the rice weed monitoring unmanned system based on Jetson TK1 provided by the present embodiment, including
It is equipped with the unmanned plane and ground control station of GPS, winged control module based on Jetson TK1, first are provided on the unmanned plane
Wireless transparent transmission module and image capture module, the first wireless transparent transmission module and image capture module are electric with winged control module respectively
Property connection, described image acquisition module includes GOPRO camera and image pick-up card, and the ground control station includes the end PC ground
It stands and the second wireless transparent transmission module, the second wireless transparent transmission module and the end PC earth station is electrically connected, the ground control station
It communicates wirelessly and connect by the first wireless transparent transmission module and the second wireless transparent transmission module with winged control module.
It is specific as follows the following are the monitoring method of the above-mentioned rice weed monitoring unmanned system of the present embodiment：
S1：Before unmanned plane takes off, monitoring area first delimited using the map function of the ground control station of independent development, and really
Determine flying height.
S2：Ground control station automatically generates unmanned plane during flying course line and needs to carry out image and adopt according to monitoring area delimited
Several destinations of collection, to guarantee that the image-capture field of GOPRO camera can cover full wafer monitoring area.
It should be noted that shown in Figure 2, offline map API delimit region ABCD, and automatically generated course line with
Destination, as destination A is equal with the image acquisition region size of destination B, and coverage area does not repeat, it is ensured that all destinations
Image-capture field can cover entire pickup area.
S3：Ground control station transmission is taken off instruction, after unmanned plane takes off, according to course line pre-planned, is flown to wanting
Carry out the destination of Image Acquisition.
S4：Unmanned plane obtains the GPS position information of next destination, flight to next destination.
S5：Unmanned plane hovers after reaching predetermined destination, and driving image capture module carries out figure to the part paddy field region
As acquisition, the winged control module based on Jetson TK1 analyzes acquired image information in real time, judges whether there is weeds
Region judges weed density grade, and pass the GPS position information and rating scale information back ground if there is weed regions
Control station.After information is sent completely, unmanned plane continues flight to next predetermined destination.
It should be noted that shown in Figure 3, P point is that one of them in course line needs to carry out the destination of Image Acquisition, square
Shape ABCD is the coverage area of the destination Image Acquisition, i.e., unmanned plane passes through destination P acquired image, and point E is by figure
As the weed regions obtained after analysis in real time, the image acquisition resolution of GOPRO moving camera is 1080*1920, and point A, point
B, point C, point D GPS coordinate it can be seen that, respectively (Alng, Alat), (Blng, Blat), (Clng, Clat), (Dlng,
Dlat), approximate region ABCD can be seen as plane right-angle coordinate, the pixel coordinate of weed regions point E in the picture is
(Ex, Ey), then the GPS coordinate of point E is equal to (Clng+ (Dlng-Clng) * (Ex/1080), Clat+ (Alat-Clat) * (Ey/
1920)), obtained weed regions GPS position information is passed back earth station by wireless telecommunications.
S6：Step S4, S5 is repeated, until unmanned plane completes all predetermined destinations.
S7：Ground control station passes through the GPS position information and density rating information for all weed regions passed back, passes through QT
With the live-action map demarcated in earth station's client that interacts of JAVASCRIPT.
It should be noted that live-action map here is developed with the offline development kit of Google Map, pass through
Html file invocation map tile shows map, is then realized using the interaction of QT Creator development platform and JAVASCRIPT
The operations such as map scaling, Orientation on map and map label.
Embodiment described above is only the preferred embodiments of the invention, and but not intended to limit the scope of the present invention, therefore
All shapes according to the present invention change made by principle, should all be included within the scope of protection of the present invention.
Claims (3)
1. the rice weed monitoring unmanned system based on Jetson TK1, including unmanned plane and ground control station, feature exist
In：Winged control module, the first wireless transparent transmission module and image capture module based on Jetson TK1 are provided on the unmanned plane,
The first wireless transparent transmission module and image capture module are electrically connected with winged control module respectively, and described image acquisition module includes
GOPRO camera and image pick-up card, the ground control station include the end PC earth station and the second wireless transparent transmission module, and described
Two wireless transparent transmission modules and the end PC earth station are electrically connected, and the ground control station and winged control module pass through the first wireless transparent transmission mould
Block and the second wireless transparent transmission module communicate wirelessly connection.
2. the rice weed monitoring unmanned system according to claim 1 based on Jetson TK1, it is characterised in that：Institute
It states unmanned plane and is equipped with GPS.
3. the monitoring method of the rice weed monitoring unmanned system described in claim 1 based on Jetson TK1, feature
It is, includes the following steps：
Before S1, unmanned plane take off, monitoring area first delimited using the map function of the ground control station of independent development, and determine and fly
Row height；
S2, ground control station automatically generate unmanned plane during flying course line and need to carry out Image Acquisition according to delimitation monitoring area
Several destinations, to guarantee that the image-capture field of GOPRO camera can cover full wafer monitoring area；
S3：Ground control station sends instruction of taking off, after unmanned plane takes off, according to airline operation pre-planned；
S4：Unmanned plane obtains the GPS position information of next destination, flight to next destination；
S5：Unmanned plane hovers after reaching predetermined destination, and the paddy field region that driving image capture module acquires needs carries out figure
As acquisition, the winged control module based on Jetson TK1 analyzes acquired image information in real time, judges whether there is weeds
Region judges weed density grade, and pass the GPS position information and rating scale information back ground if there is weed regions
Control station, after information is sent completely, unmanned plane then continues flight to next predetermined destination；
S6：Step S4, S5 is repeated, until unmanned plane completes all predetermined destinations；
S7：Ground control station passes through the GPS position information and density rating information of all weed regions passed back, by QT with
Live-action map of the interaction calibration of JAVASCRIPT in earth station's client.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810613214.4A CN108881825A (en) | 2018-06-14 | 2018-06-14 | Rice weed monitoring unmanned system and its monitoring method based on Jetson TK1 |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810613214.4A CN108881825A (en) | 2018-06-14 | 2018-06-14 | Rice weed monitoring unmanned system and its monitoring method based on Jetson TK1 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108881825A true CN108881825A (en) | 2018-11-23 |
Family
ID=64338872
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810613214.4A Pending CN108881825A (en) | 2018-06-14 | 2018-06-14 | Rice weed monitoring unmanned system and its monitoring method based on Jetson TK1 |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108881825A (en) |
Cited By (36)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109792951A (en) * | 2019-02-21 | 2019-05-24 | 华南农业大学 | For the unmanned plane course line correction system of hybrid rice pollination and its bearing calibration |
| CN109981730A (en) * | 2019-01-04 | 2019-07-05 | 哈瓦国际航空技术（深圳）有限公司 | Method, apparatus, equipment and the storage medium of ground station control unmanned plane carry |
| CN110622949A (en) * | 2019-10-22 | 2019-12-31 | 广州极飞科技有限公司 | Weeding method and device |
| CN111247496A (en) * | 2019-01-28 | 2020-06-05 | 深圳市大疆创新科技有限公司 | External load control method and device, unmanned aerial vehicle and terminal device |
| CN113126650A (en) * | 2021-03-03 | 2021-07-16 | 华南农业大学 | Automatic weeding operation method for unmanned aerial vehicle |
| US11079725B2 (en) | 2019-04-10 | 2021-08-03 | Deere & Company | Machine control using real-time model |
| US11178818B2 (en) | 2018-10-26 | 2021-11-23 | Deere & Company | Harvesting machine control system with fill level processing based on yield data |
| US11234366B2 (en) | 2019-04-10 | 2022-02-01 | Deere & Company | Image selection for machine control |
| US11240961B2 (en) | 2018-10-26 | 2022-02-08 | Deere & Company | Controlling a harvesting machine based on a geo-spatial representation indicating where the harvesting machine is likely to reach capacity |
| US20220110251A1 (en) | 2020-10-09 | 2022-04-14 | Deere & Company | Crop moisture map generation and control system |
| CN114648500A (en) * | 2022-03-17 | 2022-06-21 | 江西科技师范大学 | Crop weed detection method and device based on unmanned aerial vehicle and deep learning |
| US11467605B2 (en) | 2019-04-10 | 2022-10-11 | Deere & Company | Zonal machine control |
| US11474523B2 (en) | 2020-10-09 | 2022-10-18 | Deere & Company | Machine control using a predictive speed map |
| US11477940B2 (en) | 2020-03-26 | 2022-10-25 | Deere & Company | Mobile work machine control based on zone parameter modification |
| US11589509B2 (en) | 2018-10-26 | 2023-02-28 | Deere & Company | Predictive machine characteristic map generation and control system |
| US11592822B2 (en) | 2020-10-09 | 2023-02-28 | Deere & Company | Machine control using a predictive map |
| US11635765B2 (en) | 2020-10-09 | 2023-04-25 | Deere & Company | Crop state map generation and control system |
| US11641800B2 (en) | 2020-02-06 | 2023-05-09 | Deere & Company | Agricultural harvesting machine with pre-emergence weed detection and mitigation system |
| US11650587B2 (en) | 2020-10-09 | 2023-05-16 | Deere & Company | Predictive power map generation and control system |
| US11672203B2 (en) | 2018-10-26 | 2023-06-13 | Deere & Company | Predictive map generation and control |
| US11675354B2 (en) | 2020-10-09 | 2023-06-13 | Deere & Company | Machine control using a predictive map |
| US11711995B2 (en) | 2020-10-09 | 2023-08-01 | Deere & Company | Machine control using a predictive map |
| US11727680B2 (en) | 2020-10-09 | 2023-08-15 | Deere & Company | Predictive map generation based on seeding characteristics and control |
| US11778945B2 (en) | 2019-04-10 | 2023-10-10 | Deere & Company | Machine control using real-time model |
| US11825768B2 (en) | 2020-10-09 | 2023-11-28 | Deere & Company | Machine control using a predictive map |
| US11845449B2 (en) | 2020-10-09 | 2023-12-19 | Deere & Company | Map generation and control system |
| US11844311B2 (en) | 2020-10-09 | 2023-12-19 | Deere & Company | Machine control using a predictive map |
| US11849672B2 (en) | 2020-10-09 | 2023-12-26 | Deere & Company | Machine control using a predictive map |
| US11864483B2 (en) | 2020-10-09 | 2024-01-09 | Deere & Company | Predictive map generation and control system |
| US11874669B2 (en) | 2020-10-09 | 2024-01-16 | Deere & Company | Map generation and control system |
| US11889788B2 (en) | 2020-10-09 | 2024-02-06 | Deere & Company | Predictive biomass map generation and control |
| US11889787B2 (en) | 2020-10-09 | 2024-02-06 | Deere & Company | Predictive speed map generation and control system |
| US11895948B2 (en) | 2020-10-09 | 2024-02-13 | Deere & Company | Predictive map generation and control based on soil properties |
| US11927459B2 (en) | 2020-10-09 | 2024-03-12 | Deere & Company | Machine control using a predictive map |
| US11946747B2 (en) | 2020-10-09 | 2024-04-02 | Deere & Company | Crop constituent map generation and control system |
| US11957072B2 (en) | 2020-02-06 | 2024-04-16 | Deere & Company | Pre-emergence weed detection and mitigation system |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104320607A (en) * | 2014-08-06 | 2015-01-28 | 江苏恒创软件有限公司 | Method for monitoring growth of farmland crops based on drone |
| CN105657261A (en) * | 2015-12-30 | 2016-06-08 | 华南农业大学 | Unmanned aerial vehicle remote sensing image collection system and method based on Android device |
| CN106791596A (en) * | 2016-11-11 | 2017-05-31 | 韦红兰 | A kind of method that utilization unmanned plane is monitored to crop |
| WO2017099568A1 (en) * | 2015-12-11 | 2017-06-15 | Jose Antonio Pacheco Sanchez | Method for planning overflight of irregular polygons using two or more unmanned aerial vehicles for precision agriculture using multispectral and hyperspectral aerial image analysis |
| CN206612074U (en) * | 2017-03-24 | 2017-11-07 | 山东农业大学 | Multi-rotor unmanned aerial vehicle variable farm chemical applying device based on rice blast occurring degree |
| CN207015587U (en) * | 2017-06-02 | 2018-02-16 | 南京金快快无人机有限公司 | A kind of battery and agricultural chemicals make-up system for plant protection unmanned plane |
| CN107993226A (en) * | 2017-12-12 | 2018-05-04 | 融水苗族自治县大浪镇人民政府 | A kind of unmanned plane Cultivate administration monitoring method |
-
2018
- 2018-06-14 CN CN201810613214.4A patent/CN108881825A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104320607A (en) * | 2014-08-06 | 2015-01-28 | 江苏恒创软件有限公司 | Method for monitoring growth of farmland crops based on drone |
| WO2017099568A1 (en) * | 2015-12-11 | 2017-06-15 | Jose Antonio Pacheco Sanchez | Method for planning overflight of irregular polygons using two or more unmanned aerial vehicles for precision agriculture using multispectral and hyperspectral aerial image analysis |
| CN105657261A (en) * | 2015-12-30 | 2016-06-08 | 华南农业大学 | Unmanned aerial vehicle remote sensing image collection system and method based on Android device |
| CN106791596A (en) * | 2016-11-11 | 2017-05-31 | 韦红兰 | A kind of method that utilization unmanned plane is monitored to crop |
| CN206612074U (en) * | 2017-03-24 | 2017-11-07 | 山东农业大学 | Multi-rotor unmanned aerial vehicle variable farm chemical applying device based on rice blast occurring degree |
| CN207015587U (en) * | 2017-06-02 | 2018-02-16 | 南京金快快无人机有限公司 | A kind of battery and agricultural chemicals make-up system for plant protection unmanned plane |
| CN107993226A (en) * | 2017-12-12 | 2018-05-04 | 融水苗族自治县大浪镇人民政府 | A kind of unmanned plane Cultivate administration monitoring method |
Non-Patent Citations (1)
| Title |
|---|
| HUANG H, DENG J, LAN Y, YANG A, DENG X,: ""fully convolutional network for weed mapping of unmanned aerial vehicle (UAV) imagery"", 《PLOS ONE》 * |
Cited By (41)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11240961B2 (en) | 2018-10-26 | 2022-02-08 | Deere & Company | Controlling a harvesting machine based on a geo-spatial representation indicating where the harvesting machine is likely to reach capacity |
| US11672203B2 (en) | 2018-10-26 | 2023-06-13 | Deere & Company | Predictive map generation and control |
| US11589509B2 (en) | 2018-10-26 | 2023-02-28 | Deere & Company | Predictive machine characteristic map generation and control system |
| US11178818B2 (en) | 2018-10-26 | 2021-11-23 | Deere & Company | Harvesting machine control system with fill level processing based on yield data |
| CN109981730A (en) * | 2019-01-04 | 2019-07-05 | 哈瓦国际航空技术（深圳）有限公司 | Method, apparatus, equipment and the storage medium of ground station control unmanned plane carry |
| CN109981730B (en) * | 2019-01-04 | 2022-04-29 | 哈瓦国际航空技术（深圳）有限公司 | Method, device, equipment and storage medium for controlling mounting of unmanned aerial vehicle by ground station |
| CN111247496A (en) * | 2019-01-28 | 2020-06-05 | 深圳市大疆创新科技有限公司 | External load control method and device, unmanned aerial vehicle and terminal device |
| WO2020154834A1 (en) * | 2019-01-28 | 2020-08-06 | 深圳市大疆创新科技有限公司 | External load control method and device, unmanned aerial vehicle, and terminal device |
| CN109792951A (en) * | 2019-02-21 | 2019-05-24 | 华南农业大学 | For the unmanned plane course line correction system of hybrid rice pollination and its bearing calibration |
| US11234366B2 (en) | 2019-04-10 | 2022-02-01 | Deere & Company | Image selection for machine control |
| US11079725B2 (en) | 2019-04-10 | 2021-08-03 | Deere & Company | Machine control using real-time model |
| US11829112B2 (en) | 2019-04-10 | 2023-11-28 | Deere & Company | Machine control using real-time model |
| US11467605B2 (en) | 2019-04-10 | 2022-10-11 | Deere & Company | Zonal machine control |
| US11778945B2 (en) | 2019-04-10 | 2023-10-10 | Deere & Company | Machine control using real-time model |
| US11650553B2 (en) | 2019-04-10 | 2023-05-16 | Deere & Company | Machine control using real-time model |
| CN110622949A (en) * | 2019-10-22 | 2019-12-31 | 广州极飞科技有限公司 | Weeding method and device |
| US11641800B2 (en) | 2020-02-06 | 2023-05-09 | Deere & Company | Agricultural harvesting machine with pre-emergence weed detection and mitigation system |
| US11957072B2 (en) | 2020-02-06 | 2024-04-16 | Deere & Company | Pre-emergence weed detection and mitigation system |
| US11477940B2 (en) | 2020-03-26 | 2022-10-25 | Deere & Company | Mobile work machine control based on zone parameter modification |
| US20220110251A1 (en) | 2020-10-09 | 2022-04-14 | Deere & Company | Crop moisture map generation and control system |
| US11844311B2 (en) | 2020-10-09 | 2023-12-19 | Deere & Company | Machine control using a predictive map |
| US11650587B2 (en) | 2020-10-09 | 2023-05-16 | Deere & Company | Predictive power map generation and control system |
| US11592822B2 (en) | 2020-10-09 | 2023-02-28 | Deere & Company | Machine control using a predictive map |
| US11675354B2 (en) | 2020-10-09 | 2023-06-13 | Deere & Company | Machine control using a predictive map |
| US11711995B2 (en) | 2020-10-09 | 2023-08-01 | Deere & Company | Machine control using a predictive map |
| US11727680B2 (en) | 2020-10-09 | 2023-08-15 | Deere & Company | Predictive map generation based on seeding characteristics and control |
| US11474523B2 (en) | 2020-10-09 | 2022-10-18 | Deere & Company | Machine control using a predictive speed map |
| US11825768B2 (en) | 2020-10-09 | 2023-11-28 | Deere & Company | Machine control using a predictive map |
| US11946747B2 (en) | 2020-10-09 | 2024-04-02 | Deere & Company | Crop constituent map generation and control system |
| US11845449B2 (en) | 2020-10-09 | 2023-12-19 | Deere & Company | Map generation and control system |
| US11635765B2 (en) | 2020-10-09 | 2023-04-25 | Deere & Company | Crop state map generation and control system |
| US11849672B2 (en) | 2020-10-09 | 2023-12-26 | Deere & Company | Machine control using a predictive map |
| US11864483B2 (en) | 2020-10-09 | 2024-01-09 | Deere & Company | Predictive map generation and control system |
| US11871697B2 (en) | 2020-10-09 | 2024-01-16 | Deere & Company | Crop moisture map generation and control system |
| US11874669B2 (en) | 2020-10-09 | 2024-01-16 | Deere & Company | Map generation and control system |
| US11889788B2 (en) | 2020-10-09 | 2024-02-06 | Deere & Company | Predictive biomass map generation and control |
| US11889787B2 (en) | 2020-10-09 | 2024-02-06 | Deere & Company | Predictive speed map generation and control system |
| US11895948B2 (en) | 2020-10-09 | 2024-02-13 | Deere & Company | Predictive map generation and control based on soil properties |
| US11927459B2 (en) | 2020-10-09 | 2024-03-12 | Deere & Company | Machine control using a predictive map |
| CN113126650A (en) * | 2021-03-03 | 2021-07-16 | 华南农业大学 | Automatic weeding operation method for unmanned aerial vehicle |
| CN114648500A (en) * | 2022-03-17 | 2022-06-21 | 江西科技师范大学 | Crop weed detection method and device based on unmanned aerial vehicle and deep learning |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108881825A (en) | Rice weed monitoring unmanned system and its monitoring method based on Jetson TK1 | |
| CN108496129B (en) | Aircraft-based facility detection method and control equipment | |
| CN103941746B (en) | Image processing system and method is patrolled and examined without man-machine | |
| CN107504957B (en) | Method for rapidly constructing three-dimensional terrain model by using unmanned aerial vehicle multi-view camera shooting | |
| CN112633535A (en) | Photovoltaic power station intelligent inspection method and system based on unmanned aerial vehicle image | |
| KR101793509B1 (en) | Remote observation method and system by calculating automatic route of unmanned aerial vehicle for monitoring crops | |
| CN110134147A (en) | A kind of autonomous paths planning method and device of plant protection drone | |
| CN108694882A (en) | Method, apparatus and equipment for marking map | |
| Spachos et al. | Integration of wireless sensor networks and smart uavs for precision viticulture | |
| CN105046909A (en) | Agricultural loss assessment assisting method based on small-sized unmanned aerial vehicle | |
| CN112489130A (en) | Distance measuring method and device for power transmission line and target object and electronic equipment | |
| CN110223386A (en) | A kind of digital terrain modeling method based on multi-source unmanned aerial vehicle remote sensing data fusion | |
| CN109032174B (en) | Unmanned aerial vehicle operation route planning method and operation execution method | |
| CN112113542A (en) | Method for checking and accepting land special data for aerial photography construction of unmanned aerial vehicle | |
| CN113075938A (en) | Remote intelligent inspection system and method for power transmission line | |
| CN112702565A (en) | System and method for acquiring field plant phenotype information | |
| CN208027170U (en) | A kind of power-line patrolling unmanned plane and system | |
| CN207835662U (en) | One kind being based on Embedded unmanned aerial vehicle remote sensing image capturing system | |
| CN107390699A (en) | The route planning system and its route planning method of a kind of sugarcane planting machine | |
| CN105389555A (en) | Aerial-image-based hidden-danger target analysis method and system | |
| CN112729248A (en) | Remote sensing detection system and method based on unmanned aerial vehicle platform | |
| CN113610040B (en) | Paddy field weed density real-time statistical method based on improved BiSeNetV2 segmentation network | |
| CN115861859A (en) | Slope farmland environment monitoring method and system | |
| US20220330468A1 (en) | System and methods for gathering data relating to crops and for managing crop growing operations | |
| CN113807309B (en) | Deep learning-based orchard machine walking route planning method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20181123 |